TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101-40, February 2021.

Assessment of the Competitive Positions of National of

Ovsak Oksana Pavlivna, Liskovych Nazarii Yuriiovych, Nazarenko Oleksandra Pavlivna

National Aviation University, Lubomir Guzar Avenue, 1, . 03058, Ukraine

Abstract – This article presents the results of International publications contain many publications systematization of methodological basis for assessing on the definition of strategic groups of enterprises, in the competitive status of domestic airlines in the particular airlines: Tang M, Thomas H. [1], Kling J. absence of information about their financial condition, A., Smith K. A. [2], Ketchen D.R, Shook C.L. [3], actually due to cluster analysis of their various DesarboW.S. and Grewal R. [4]. Researchers Murthi operational, communication and marketing characteristics. Based on the results comprising B.P.S., RasheedA. A. and Goll I. revealed the cluster analysis of profile indicators of airlines features of using the regression model of the latent available from open sources, clusters - strategic groups class to identify strategic groups of American airlines of Ukrainian airlines were identified. Construction of a [5]. Unfortunately, these scientific and competitive map of the air transportation market of methodological works cannot be used to assess Ukraine, identification of clusters of domestic airlines competition and identify strategic groups in countries provide an opportunity to use a differentiated with underdeveloped financial markets, such as approach to the tools of strategic positioning and crisis Ukraine. This is due to the insufficiently public management of airlines of Ukraine. financial statements of the national airlines of Keywords – , strategic airline groups, cluster Ukraine, because only three of them – PJSC analysis, competitive position. “Ukraine International Airlines”, PJSC “Bukovina”, JSC “Motor Sich” are joint-stock companies whose 1. Introduction reports are publicly available. Other airlines (16) are limited liability companies in their legal form and do Today, the most well-known and widely used tool not publish their financial statements. for identifying the competitive position of enterprises Most often, experts in the transport and aviation in a particular industry is cluster analysis, which industry recommend using the M.Porter approach, allows statistical methods to distribute the studied according to which it is advisable to form strategic objects with similar characteristics into the groups of competing firms that use similar corresponding individual groups (clusters). competitive approaches and positions in the Market [6]. In accordance with this methodological approach, a study by Kling J. A. and Smith K. A. was DOI: 10.18421/TEM101-40 conducted regarding the definition of strategic groups https://doi.org/10.18421/TEM101-40 of American Airlines [2]. In our research to Corresponding author: Ovsak Oksana Pavlivna, determine the competitive position of airlines in the National Aviation University, Lubomir Guzar Avenue, 1, absence of information about their financial position Kyiv. 03058, Ukraine. we used the methodological approaches of M.Porter, Email: [email protected] G. Azoev and A.Chelenkov [6], [7] to build a Received: 15 November 2020. competitive market map and identify strategic groups Revised: 03 February 2021. of national airlines of Ukraine based on their diverse Accepted: 10 February 2021. operational, communication as well as marketing Published: 27 February 2021. characteristics. © 2021 Ovsak Oksana Pavlivna, Liskovych Nazarii Yuriiovych & Nazarenko Oleksandra Pavlivna; 2. Analysis of the State of Competition in the published by UIKTEN. This work is licensed under the Ukrainian Air Transportation Market Creative Commons Attribution‐NonCommercial‐NoDerivs To analyze the market competition in which 4.0 License. Ukrainian airlines operate, the Porter Five Forces The article is published with Open Access at model was used, which is based on the concept that www.temjournal.com there are five competitive forces that determine the competitive environment and intensity combined

318 TEM Journal – Volume 10 / Number 1 / 2021. TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101‐40, February 2021. with the attractiveness of the market [8]. Porter's Five 3) The threat of new competitors in the aviation Forces Analysis is considered appropriate to identify market: sources of competitive advantage in the business . For airlines - the presence of both barriers to environment, which in turn is crucial for determining entry to the market for new domestic airlines, the airline's competitive position and possible future and barriers to access to new international strategy based on the competitive position – its markets (economic, administrative and legal); strategic position. In addition, M. Porter claims that . The need for experience in managing an aviation commercial aviation is one of the toughest markets business, while at the same time training options with the lowest profit margins and the strongest are available. Due to the introduction of anti- forces, and established competitors compete pandemic measures at the state level, passenger vigorously with each other in terms of price and flights were suspended, and there is a possibility customers. He even highlights the importance of of a long-term crisis due to a decrease in demand analyzing the five competitive forces, as it allows for reasons of caution, even if restrictions on air airlines to see an overall competitive picture of what traffic are lifted. There is a possibility of the exactly drives the industry's profitability. emergence of a low-budget domestic carrier, The analysis of the development of the Ukrainian whose aircraft fleet will consist of domestic- air transportation market allowed us to form columns made aircraft. of the matrix of competitive advantages for five key 4) The threat of air travel replacement services: factors of competition in the industry: the market . In Ukraine, other types of transport are an power of consumers of transport services, the market alternative to domestic air transportation, power of suppliers, the threat of new competitors in sometimes external (their cost, convenience, the aviation market and competition between quality, safety, habits, etc. determine the competing airlines. They were gradually parameters of consumer choice). It should be systematized below. borne in mind that the cost of traveling by rail in Ukraine is cheaper than by air. The development 1) Market power of consumers of air transport of airport infrastructure and ease of access to the services: airport are important parameters. However, due . Due to the introduction of anti-pandemic to the emergence of the pandemic (COVID19), measures at the state level, passenger flights the safety of travel, stay in the destination were suspended, and there is a possibility of a country and the availability of reliable medical long-term crisis due to a decrease in consumer care on air travel turned out to be factors, the demand due to caution, even if the countries' lack of guarantees of which (and their cost) restrictions on air traffic are lifted. Spontaneous determine the choice of consumers in favor of weekend short-distance travel may decrease due video meetings, video conferences and other to the difficulty of traveling during this period. innovative ways of conducting business 2) Market power of suppliers: communications. There is a tendency to replace . Airlines' dependence on airport infrastructure long-distance air travel with close, well-known development; destinations. . Limited availability of domestic airlines to 5) Rivalry between competing airlines: modern aircraft on affordable financial terms; . Weighing the action of the above four . The presence of a monopoly power of aviation competitive forces, the rivalry between fuel suppliers in the domestic market of Ukraine; competing airlines, mainly between airlines, . The presence of risks of increasing lease becomes particularly acute. Due to the gradual payments for the use of aircraft, significant liberalization of bilateral interstate agreements, amounts of deductions for aircraft maintenance, there is an increase in competition with foreign even with temporary non-use. At the same time, airlines (both network and low-budget) in the due to the emergence of the pandemic (COVID market in general and routes in particular. There 19), there are opportunities to receive aircraft on is increasing competition for leadership in the affordable terms due to a decrease in the demand regular seasonal and charter air transportation of foreign airlines for aircraft, receiving aircraft sector. At the same time, integration processes on sublease terms from partner airlines; are developing among leading airlines (“Ukraine . The presence of a monopoly power of aviation International Airlines”, “Wind Rose”), as well as fuel suppliers in the domestic market of Ukraine, among airlines and business partners, in which contributes to maintaining a high level of particular travel companies (“SkyUp Airlines prices; LLC” and “Join UP!” travel companies). . Lack of a well-developed system of mutual settlements with partners in the aviation business Table 1 shows the dynamics of the number of (airlines, travel operators, hotels, etc.). flights performed by airlines that provide the largest

TEM Journal – Volume 10 / Number 1 / 2021. 319 TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101‐40, February 2021. volumes of air navigation services, including the Using the constructed Table 2, the analysis of the following: “Ukraine International Airlines”, “Turk dynamics of the market share of airlines with the Hava Yollari A.O.”, “Belavia”, “LOT Polish most significant volumes of providing aviation Airlines”, “ LLC”, “Wind Rose”, services in the aviation market of Ukraine has been “Pegasus”, “Air Moldova”, “Azur ”, carried out. “Austrian Airlines AG”, “Qatar Airways”, “SkyUp Analysis of the dynamics of the market share of Airlines LLC” and “Ryanair”. airlines with the most significant volumes of providing aviation services in the Ukrainian aviation Table 1. Dynamics of the most significant volumes of air market showed that in 2019 there was a rapid decline navigation services for airlines in the market shares of leading network airlines:

Number of flights “Ukraine International Airlines”, “Turk Hava Yollari Airlines 2016 2017 2018 2019 A.O.”, “Air Moldova”, the market position is “Ukraine maintained such airlines as: “Belavia”, “LOT Polish International 49145 57205 61691 58772 Airlines”, “Wind Rose”, “”, Airlines” Turk Hava “Austrian Airlines AG” and “Qatar Airways”. There 22928 27606 29972 33716 Yollari A.O. was a rapid growth in the market shares of such “Belavia” 12796 14537 16003 18629 airlines: “SkyUp Airlines LLC”, “Ryanair” and “LOT Polish “Wizz Air Hungary LLC”, moreover, the last two are 9903 12756 15813 18449 Airlines” well – known European low-cost carriers. As the “Wizz Air 5625 8832 15251 20944 analysis of Table 2 showed for each year, we can Hungary LLC” distinguish three leading airlines, each of which had “Wind Rose” 3519 8162 9 301 10185 shares above 10%, as well as five leading airlines, “Pegasus” 4289 5825 7 664 5569 “Air Moldova” 4219 5527 7 224 5423 each of which had shares above 5%. “Azur Air The analysis carried out on the basis of statistical 4073 4607 4 859 7229 Ukraine” information does not make it possible to form an idea “Austrian 3205 3751 3687 3787 of the state of affairs in the air transportation market, Airlines AG” so it became advisable to identify strategic groups of “Qatar 1589 1985 4673 5893 Airways” national airlines based on data from open sources and “SkyUp content analysis of airline reports and websites. This - - 2411 10631 Airlines LLC” will make it possible to use a differentiated approach “Ryanair” - - 1728 9295 to the tools of strategic positioning of Ukrainian Total 121 291 150 793 180 277 208 522 airlines as well as areas and tools of anti-crisis Source: (Reports of the state enterprise “Ukraerorukh”, management.

2017-2020), [9]

Table 2. Dynamics of the market share of airlines with the most significant volumes of providing aviation services in the Ukrainian aviation market

Market Market Growth rate Market Growth rate Market Growth rate Airlinesї share share market share share market share share market share 2016 2017 2017/2016 2018 2018/2017 2019 2019/2018 Ukraine Internatio- 0,41 0,38 -7,32% 0,34 -10,53% 0,28 -17,65% nal Airlines Turk Hava Yollari 0,19 0,18 -5,26% 0,17 -5,56% 0,16 -5,88% Belavia 0,11 0,10 -9,09% 0,09 -10,00% 0,09 0,00% LOT Polish Airlines 0,08 0,08 0,00% 0,09 12,50% 0,09 0,00% Wizz Air Hungary 0,04 0,06 50,00% 0,08 33,33% 0,1 25,00% LLC Wind Rose 0,03 0,05 66,67% 0,05 0,00% 0,05 0,00% Pegasus 0,04 0,04 0,00% 0,04 0,00% 0,03 -25,00% Air Moldova 0,03 0,04 33,33% 0,04 0,00% 0,03 -25,00% Azur Air Ukraine 0,03 0,03 0,00% 0,03 0,00% 0,03 0,00% Austrian Airlines AG 0,03 0,02 -33,33% 0,02 0,00% 0,02 0,00% Qatar Airways 0,01 0,01 0,00% 0,03 200,00% 0,03 0,00% SkyUp Airlines LLC - 0,01 0,05 400,00% Ryanair - 0,01 0,04 300,00%

320 TEM Journal – Volume 10 / Number 1 / 2021. TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101‐40, February 2021.

3. Methodology and Data transportation, the number of aircraft fleet, punctuality of the airline, the availability of loyalty As the analysis of sources has shown, cluster programs. Taking into account the specifics of the analysis allows using statistical methods to distribute activities of domestic airlines, it is advisable to the studied objects with similar features into the include in the list of such indicators the presence of corresponding individual groups (clusters) [10], [11]. integration interactions of such an airline with Cluster analysis uses various types of coefficients: partners in the aviation business and the state of correlations, distance indicators, associativity and mutual settlements with them. To perform a cluster probability, as well as similarity coefficients. The use analysis of the characteristics of Ukrainian airlines, of each of these coefficients has its own advantages their profile indicators were used which are obtained and disadvantages, which has to first be taken into from open sources and systematized in Table 3. account [12], [13]. In the practice of cluster analysis Designations relative to Table 3 are presented below. of economic characteristics of enterprises, when Var.1 - type of air transportation (passenger (pass), determining the degree of similarity of these objects, cargo, mixed); the most common are correlation coefficients and Var.2 - type of flights operated (regular and charter Euclidean distances [2], [11]. As a result of - 3, charter - 1); analyzing the set of input data, homogeneous groups Var.3 - share of regular flights (more than 50% are formed in such a way that objects within these regular "2"; more than 50% regular charter - 2, groups are similar to each other in a certain set of more than 50% charter - 0.5); features, and objects from different groups (clusters) Var.4 - use of global distribution systems for the differ significantly from each other. When sale of air transportation (1-available. 0-missing); performing cluster analysis of the studied objects, Var.5 - annual number of flights (up to 7,000 one of the most important tasks is to select a set of flights - "1", 7000-15000 - "2" more than 15,000 their features, which are taken as the basis for their flights "3"); assessment. The purpose of this stage of analysis is to Var.6 - number of aircraft in operation (up to 5 determine the set of variable features that most fully aircraft "1", 5-15 "2", more than 15 aircraft "3"); reflects the similarity or difference of the specified Var.7 - average age of the aircraft fleet (up to 10 objects. These attributes have to meet the conditions years "3", 10-20 years "2", more than 20 years of the selected classification of objects, as well as the "1"); final purpose of the analysis. Therefore, cluster Var.8 - airline punctuality (up to 80% "1", 80-90% analysis should be carried out on the basis of the "2", more than 90% "3") Var.9 - availability of values of key indicators that are related to the integration interactions (availability of all possible corresponding state of development of the airline, interactions - "3" mixed with travel agencies, or due to the peculiarities of its business processes. with airlines "2", transactions only with cargo The analysis of the peculiarities of airlines' agents - "1"); activities showed that such key indicators of Var.10 - loyalty programs (presence of "1" or domestic airlines should include: the type and types absence of "0"); of air transportation performed, the share of regular Var.11 - timely settlements with business partners flights, the annual number of flights, the use of and clients (presence of "1" or absence of "0") global distribution systems for the sale of air

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Most domestic airlines operating in the Thus, cluster analysis is performed with the international air transportation market are limited calculation of the Euclidean distance matrix "C" for liability companies in their organizational and legal the studied objects, taking into account their profile form, so their financial indicators, as well as cost- indicators. The method is based on the analysis of effectiveness indicators, are not publicly available. this square and symmetric with respect to the main Joint-stock airlines are «Ukraine International diagonal of the matrix, which has the following form. Airlines», «Bukovina» and «Motor Sich» airlines.  0 C(1,2) ... C(1, p)  A measure of determining the proximity of objects   to the possibility of combining them in a common  C(2,1) 0 ... C(2, p) C  (1) cluster is the Euclidean distance calculated from the  ......  values of their key indicators. When identifying     airline and airport clusters, it is also advisable to use C( p,1) C( p,2) ... 0  a set of dummy variables that reflect the absence or and consists of elements, namely, Euclidean presence of certain characteristics for an airline with distances C (i, j) between the corresponding profile the values "0" and "1", respectively. indicators of objects.

Table 3. Profile indicators of Ukrainian Airlines (prepared for software processing)

Var Var. № Airline Var.1 Var.2 Var.3 Var.3 Var.5 Var.6 Var.6 Var.8 Var.9 10 11 PJSC “Ukraine 1 Іnternational mixed 3 2 1 3 3 3 3 3 1 1 Airlines” 2 “Wind Rose LLC” pass 3 1 0 2 2 2 2 2 1 1 3 “SkyUp Airlines” pass 3 1 0 2 2 2 2 1 1 1 4 «Azur Air Ukraine» pass 3 1 0 2 2 2 2 1 1 1 5 “ Airlines” pass 3 0,5 0 1 2 1 2 1 0 0 6 “” pass 3 0,5 0 1 2 1 2 1 0 0 Separate division 7 airline of PJSC mixed 3 1 0 1 2 1 2 2 0 1 “Motor Sich” 8 PJSC “Bukovina” mixed 3 1 0 1 1 2 2 2 0 1 9 “JONIKA Airlines” pass 3 0,5 0 1 1 2 1 1 0 0 10 “” pass 3 1 0 1 1 3 3 1 0 1 “AtlasGlobal 11 pass 3 1 0 1 1 2 2 1 0 1 Ukraine” 12 Airline “Khors” mixed 1 0,5 0 1 2 1 2 1 0 1 13 “ Airlines” mixed 1 0,5 0 1 2 1 2 1 0 1 Aviation transport 14 company cargo 1 0,5 0 1 2 1 2 1 0 1 “Yuzmashair” 15 “Anda-Air” Airline pass 1 0,5 0 1 1 1 1 1 0 1 16 “UM Аir” Airline mixed 1 0,5 0 1 1 1 2 1 0 1 17 CAVOK Airlines cargo 1 0,5 0 1 1 1 2 1 0 1 “Antonov” State 18 cargo 1 0,5 0 1 3 2 3 1 0 1 enterprise Aircompany 19 cargo 1 0,5 0 1 2 1 2 1 0 1 “ZetAvia” 20 “Maximum Air ” cargo 1 0,5 0 1 2 1 2 1 0 1 21 “Meridian” airline mixed 1 0,5 0 1 1 1 2 1 0 1 22 “Aero-charter” mixed 1 0,5 0 1 1 1 2 1 0 1 23 “Mars RK” mixed 1 0,5 0 1 1 1 2 1 0 1

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Table 4. Estimated ratio scale comparison matrix is formed, which is presented in Relative Table 5. weight of the Element characteristics element A special feature of such a matrix is the characteristic fulfillment of the relationship between its elements: , 1 Equilibrium ratio where i – matrix row numbering, j – numbering of its A very small advantage of one over columns. 2 the other The elements of this comparison matrix are A slight advantage of one over the numerical values of the manifestation of the 4 other significance of indicators relative to each other A noticeable advantage of one over 6 When filling in the matrix, pairs of indicators that the other were located above the diagonal of the matrix were A significant advantage of one over 8 compared, for which pairs of the same indicators the other have a single value of relative significance. The Strong advantage of one over the 10 values of elements placed below the diagonal of the other Matrix were automatically filled with values that are A very strong advantage of one over 12 the other the inverse of the values for the corresponding pairs 3, 5, 7, 9, 11 Intermediate values of indicators placed above the diagonal of the matrix (Table 5). When determining the eigenvector Elements C (i, j) of the matrix are calculated based components for each indicator the geometric mean on the values of profile indicators of objects by the Xgeom of all numbers in the corresponding k row of expression: the comparison matrix was calculated:

Nk n C(i, j)  (A(i,k)-A(j,k))2 , Xgeom ki  Ak1  Ak 2 ...  Akn , (3) k1 (2)

where Aki – the i- ordinal element in the matrix where A (i, k), A (j, k), - corresponding values of row profile indicator. profile indicators; Finally, the components of the eigenvector of the i, j - sequence numbers of profile indicators; matrix are normalized as the ratio of each geometric Nk - total number of profile indicators used for mean component of Xgeomk to their sum (5) analysis. n When conducting the cluster analysis, we used an Xsum   Xgeomk (4) array of profile indicators (parameters) that k1 characterize Ukrainian airlines, taking into account their informative content, as well as based on the k Xgeomk availability of information about them in open S  , (5) wei Xsum sources. Given the significant differences in the absolute values and conceptual essence of these that is, weighting factors are obtained for each of the ki - profile indicators, which are presented in the indicators, according to the cluster analysis fourth column of Table 6 comparisons related to the methodology, it is necessary to determine the degree corresponding of importance of each of them by using a weighting According to the method of hierarchical analysis of factor. For this task, the paper uses the method of T. Saaty [16], the degree of violation of the analyzing hierarchies of Thomas Saaty, because it consistency of elements of the calculated comparison allows to analyze complex systems using mixed matrix is characterized by the consistency index Iy, quantitative and qualitative indicators (profile determined from the expression: indicators) [14], [15], [16], according to which the relative importance of indicators is determined by ( max  n) their pairwise comparison. For this purpose, the Ic  , (6) evaluation scale of pairwise ratios from the method (n 1) of T. Saaty is taken as a basis, which was modified to where – largest eigenvalue of the matrix, an extended 12-point gradation, as shown in Table 4. n – the number of profile indicators used and, Numerical values of the relative significance of the accordingly, is the dimension of the matrix. influence of each of the pairs of profile indicators on A measure of the degree of deviation of the the airline's characteristics are determined using the comparison matrix from consistency is the value of above method and using the values of paired the relative consistency of the Zrl: comparisons, an inversely symmetric diagonal

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Table 5. Determination of weight coefficients of profile indicators of Ukrainian airlines

Normalized Code of eigenvector

indicators and 10 11 (indicator Var. Var. Var. Own Own Var.2 Var.2 Var.3 Var.4 Var.5 Var.6 Var.7 Var.8 Var.9 vectors vector weighting factor) Var.2 1 1 4 1 3 4 4 8 9 9 2,884 0,206 Var.3 1 1 4 1 3 4 4 8 9 9 2,884 0,206 Var.4 0,25 0,25 1 0,333 0,333 3 3 7 10 10 1,178 0,084 Var.5 1 1 3 1 3 6 6 9 11 11 3,167 0,226 Var.6 0,333 0,333 3 0,333 1 8 8 8 11 11 2,045 0,146 Var.7 0,250 0,250 0,333 0,167 0,125 1 2 2 10 10 0,637 0,046 Var.8 0,250 0,250 0,333 0,167 0,125 0,5 1 9 10 10 0,646 0,046 Var.9 0,125 0,125 0,143 0,111 0,125 0,500 0,111 1 11 11 0,299 0,021 Var.10 0,111 0,111 0,1 0,091 0,091 0,1 0,1 0,091 1 1 0,128 0,009 Var.11 0,111 0,111 0,1 0,091 0,091 0,1 0,1 0,091 1 1 0,128 0,009

Ic row of the Euclidean distance matrix for Ukrainian Z  , Airlines shows the proximity of the characteristics of rl I (7) oc the corresponding object to similar characteristics of other objects. where Ioc – is the consistency index of a square In Table 7, the minimum values of Euclidean matrix of order k, formed randomly. The values of distances between the corresponding pairs of objects, this value should not exceed 10%. indicating the proximity of their corresponding profile indicators, are highlighted in different 4. Results and Discussions background colors and red font, which made it possible to include them in joint strategic groups Based on the results of cluster analysis, the profile (clusters). As a result of calculations for Ukrainian indicators were distributed according to Division airlines (formulas (3) – (7)), the values of the scales, normalized, and their weighting coefficients maximum eigenvalue of the comparison matrix were ki were determined, as shown in Table 5 and Table 6. calculated (and the corresponding consistency index The calculated Euclidean distance matrices for the Ic= 0,1239. According to the work of Thomas Saaty studied Ukrainian airlines are shown in Table 7. The [13], for a randomly generated matrix with an ordinal airline's ordinal number in Table 6 corresponds to its number k=10, the value of the average random ordinal number in Table 3. A Mathematical sample consistency Index is Ioc=1,49. of the smallest values among the elements in each

Table 6. Profile indicators of Ukrainian airlines, their distribution on the division scale and weight coefficients

Indicator weight № Indicator name Assigning values to indicators on a division scale factor (normalized eigenvector) Var.2 Type of flights performed regular and charter flights – “3”, charter flights - “1” 0,206 more than 50% regular “2”; more than 50% regular Var.3 Share of scheduled flights 0,206 charter - 2, more than 50% charter - 0.5 Using global distribution systems Var.4 “1” - used, “0” - not used 0,084 for air transportation sales Up to 7,000 flights - “1”, 7000-15000 - “2”, more than Var.5 Annual number of flights 0,226 15,000 flights “3” Number of passenger vessels in Var.6 Up to 5 planes “1”, 5-15- “2”, more than 15 aircraft “3” 0,146 operation Up to 10 years “3”, 10-20 years “2”, more than 20 Var.7 Average age of the aircraft fleet 0,046 years “1” Var.2 Airline punctuality up to 80% “1”, 80-90% “2”, more than 90% “3” 0,046 availability of various agreements (with travel Availability of integration agencies, agents, other airlines - “3”, availability of Var.8 0,021 interactions agreements with travel agencies, or with airlines “2”, availability of agreements only with cargo agents - “1” Var.9 Loyalty programs presence of “1” or absence of “0” 0,009 Timely mutual accounts with Var.10 presence of “1” or absence of “0” 0,009 business partners and clients

324 TEM Journal – Volume 10 / Number 1 / 2021. TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101‐40, February 2021.

Calculated using the obtained values by expression Other domestic airlines make up four more (6), the value of Zrl=8,31%. It is less than 10%, clusters. To the second group called "Network hybrid therefore, the consistency of the comparison matrix airlines» only one was included - the most powerful obtained for the profile indicators of Ukrainian national airline “Ukraine International Airlines”. The Airlines corresponds to the norm. third strategic group, called "Leading hybrid It should be noted that the calculation and analysis airlines", includes the following: “SkyUp Airlines of the Euclidean distance matrix for Ukrainian LLC”, “Azur Air Ukraine”, “Wind Rose”. The third airlines was performed using specially developed strategic group, called "Secondary hybrid airlines", computer program codes in the Fortran 90 consists of the following: “Wizz Air Ukraine”, environment and the calculations of eigenvalues of “JONIKA Airlines”, “PJSC “Bukovina”, “YanAir comparison matrices were carried out using a Airlines”, “Bravo Airways”. “AtlasGlobal Ukraine”, complex of calculations of mathematical algorithms “Motor Sich”. The fifth cluster, called "Charter Wolfram Mathematics. airlines", consists of the following small airlines: So, the cluster analysis revealed five strategic groups “”, “UM Airlines”, “Meridian” airline, (clusters) of Ukrainian airlines. The first cluster is “Aero-charter”, “Mars RK”. represented by a group of cargo airlines formed only Based on the analysis of the development of the by the values of indicator 1 (see Table. 3). Ukrainian air transportation market, as well as content analysis of open data on the activities of Table 7. Euclidean distance matrix for Ukrainian Airlines domestic and foreign airlines in the Ukrainian air

1234567891011121314151617181920212223 transportation market (Tables 1, 2), a competitive Airline ' number 1 0 0,34 0,35 0,35 0,55 0,55 0,5 0,55 0,61 0,55 0,56 0,68 0,68 0,68 0,73 0,73 0,73 0,65 0,68 0,68 0,73 0,73 0,73 map of the Ukrainian air transportation market by 20,3400,03 0,03 0,23 0,23 0,21 0,25 0,28 0,26 0,25 0,46 0,46 0,46 0,49 0,49 0,49 0,49 0,46 0,460,490,490,49 30,350,03 0 0 0,23 0,23 0,21 0,25 0,27 0,26 0,25 0,46 0,46 0,46 0,49 0,48 0,48 0,48 0,46 0,460,480,480,48 airline has been compiled (Table 8). 40,350,03 0 0 0,23 0,23 0,21 0,25 0,27 0,26 0,25 0,46 0,46 0,46 0,49 0,48 0,48 0,48 0,46 0,46 0,48 0,48 0,48 5 0,55 0,23 0,23 0,23 0 0 0,1 0,19 0,17 0,21 0,19 0,4 0,4 0,4 0,43 0,43 0,43 0,43 0,4 0,4 0,43 0,43 0,43 6 0,55 0,23 0,23 0,23 0 0 0,1 0,19 0,17 0,21 0,19 0,4 0,4 0,4 0,43 0,43 0,43 0,43 0,4 0,4 0,43 0,43 0,43 7 0,5 0,21 0,21 0,21 0,1 0,1 0 0,16 0,2 0,19 0,16 0,41 0,41 0,41 0,44 0,44 0,44 0,45 0,41 0,41 0,44 0,44 0,44 8 0,55 0,25 0,25 0,25 0,19 0,19 0,16 0 0,12 0,08 0,03 0,44 0,44 0,44 0,42 0,42 0,42 0,51 0,44 0,44 0,42 0,42 0,42 9 0,61 0,28 0,27 0,27 0,17 0,17 0,2 0,12 0 0,15 0,11 0,43 0,43 0,43 0,4 0,41 0,41 0,51 0,43 0,43 0,41 0,41 0,41 10 0,55 0,26 0,26 0,26 0,21 0,21 0,19 0,08 0,15 0 0,07 0,45 0,45 0,45 0,44 0,43 0,43 0,51 0,45 0,45 0,43 0,43 0,43 11 0,56 0,25 0,25 0,25 0,19 0,19 0,16 0,03 0,11 0,07 0 0,44 0,44 0,44 0,42 0,42 0,42 0,51 0,44 0,44 0,42 0,42 0,42 12 0,68 0,46 0,46 0,46 0,4 0,4 0,41 0,44 0,43 0,45 0,44 0 0 0 0,16 0,15 0,15 0,17 0 0 0,15 0,15 0,15 13 0,68 0,46 0,46 0,46 0,4 0,4 0,41 0,44 0,43 0,45 0,44 0 0 0 0,16 0,15 0,15 0,17 0 0 0,15 0,15 0,15 14 0,68 0,46 0,46 0,46 0,4 0,4 0,41 0,44 0,43 0,45 0,44 0 0 0 0,16 0,15 0,15 0,17 0 0 0,15 0,15 0,15 15 0,73 0,49 0,49 0,49 0,43 0,43 0,44 0,42 0,4 0,44 0,42 0,16 0,16 0,16 0 0,05 0,05 0,32 0,16 0,16 0,05 0,05 0,05 16 0,73 0,49 0,48 0,48 0,43 0,43 0,44 0,42 0,41 0,43 0,42 0,15 0,15 0,15 0,05 0 0 0,31 0,15 0,15 0 0 0 17 0,73 0,49 0,48 0,48 0,43 0,43 0,44 0,42 0,41 0,43 0,42 0,15 0,15 0,15 0,05 0 0 0,31 0,15 0,15 0 0 0 18 0,65 0,49 0,48 0,48 0,43 0,43 0,45 0,51 0,51 0,51 0,51 0,17 0,17 0,17 0,32 0,31 0,31 0 0,17 0,17 0,31 0,31 0,31 19 0,68 0,46 0,46 0,46 0,4 0,4 0,41 0,44 0,43 0,45 0,44 0 0 0 0,16 0,15 0,15 0,17 0 0 0,15 0,15 0,15 20 0,68 0,46 0,46 0,46 0,4 0,4 0,44 0,43 0,45 0,44 0 0 0 0,16 0,15 0,15 0,17 0 0 0,15 0,15 0,15 21 0,73 0,49 0,48 0,48 0,43 0,43 0,44 0,42 0,41 0,43 0,42 0,15 0,15 0,15 0,05 0 0 0,31 0,15 0,15 0 0 0 22 0,73 0,49 0,48 0,48 0,43 0,43 0,44 0,42 0,41 0,43 0,42 0,15 0,15 0,15 0,05 0 0 0,31 0,15 0,15 0 0 0 23 0,73 0,49 0,48 0,48 0,43 0,43 0,44 0,42 0,41 0,43 0,42 0,15 0,15 0,15 0,05 0 0 0,31 0,15 0,15 0 0 0

Table 8. Competitive map of the Ukrainian air transportation market (Airlines)

Airline groups Airline market Airlines with a share Market Airlines with a weak Market strong competitive Market share leaders competitive position outsiders position growth rate, % 1 2 3 4 “Czech Airlines”, “Air Astana”, “Air France”, “Air “Ryanair”, “SkyUp “Ernest Airlines”, Malta”, “Air Serbia”, Rapid growth 1 - Airlines LLC” “Ellinair” “АirBaltic”, “El Al”,”

Flydubai”, “Georgian Airways”, “Iraqi Airways” “Swiss International Air Lines”, “Scandi-navian “LOT Polish Airlines” Airlines”, “Anda Air”, Moderate growth 2 - “Buta Airways” “Azur Air Ukraine”, “Meridian” airline “TAROM”, “Onur Air”, “Qatar Airways” “Alitalia”, “Aegean Airlines” “UM Аir” “Belavia”, “KLM”, “Lufthansa”, “Turk Hava Airline, “AERO- Moderate decline 3 “Wind Rose”, “AtlasGlobal Ukraine”, Yollari A.O.” CHARTER”, “Austrian Airlines” “Bukovina” “MARS RK”. “YanAir Airlines”, “Bravo “Ukraine “Pegasus”, “Air Airways”, “JONIKA Rapid decline 4 International Moldova” Airlines”, “Wizz Air Airlines” Ukraine”

TEM Journal – Volume 10 / Number 1 / 2021. 325 TEM Journal. Volume 10, Issue 1, Pages 318‐326, ISSN 2217‐8309, DOI: 10.18421/TEM101‐40, February 2021.

5. Conclusions References

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